Many applications of digital video rely on the use of data compression. Sampled video source signals require byte rates from 10 megabytes per second for broadcast-quality video to more than 100 megabytes per second for high definition television signals. Even when still pictures are involved, as in image archival systems, large quantities of data are needed to represent them.
There are two known methods which actually reduce the quantity of data to be transmitted:
1) Quantization, and PA1 2) Statistical Coding (e.g., Huffman coding).
All digital video transmission systems require both sampling and quantization. The quantization step necessarily introduces distortion but, if carried out using an error criterion based on visual perception, is not disturbing to the viewer. For example, scalar quantization of luminance to words of 256 states cannot be detected. Vector Quantization (VQ) is an extension of this process in which symbols are assigned to groups of video samples according to their joint probability of occurrence. An error criterion based on acceptability to the viewer is used. Where certain combinations of sample values occur with much higher probability than others, VQ achieves a significant reduction in the amount of data transmitted.
Statistical Coding operates on samples that are already quantized. It is the process of assigning optimum length code words to sample values according to their probability of occurrence. Frequently occurring symbols are assigned short code words, while infrequently occurring symbols are assigned longer code words.
Statistical Coding and Vector Quantization are not mutually exclusive. For example, VQ can be used as the initial quantizer feeding a Statistical Coding algorithm.
The effectiveness of either VQ or Statistical Coding can be improved by supporting techniques that decrease the apparent entropy of the signal. These supporting techniques include predictive coding, transform coding, and sub-band coding.
Predictive coding employs a predictor employing previously received signals to estimate a sample value. The transmitted signal consists of symbols representing the difference between the actual value and the estimate. The RMS value of the error signal is thereby decreased. Since prediction of low spatial frequencies is typically more accurate than that of high spatial frequencies, the error signal consists mainly of high frequency information.
Transform coding (using, e.g., a discrete cosine transform (DCT)) is another technique that can decrease the entropy of the data to be coded. Real images usually have shaded areas containing only small amounts of high spatial frequencies. A two-dimensional cosine transform of the image blocks tends to generate large coefficients only close to the zero frequency coefficient. These two techniques are often combined by applying DCT to the error signal generated through predictive coding.
Sub-band coding divides the signal into separate bands, (e.g., frequency bands). Each band has a lower entropy than the original, and may be coded using the technique most applicable to that band.
In all cases, the final step must be a Vector Quantization or Statistical Coding operation which actually reduces the data rate. In an example of one Vector Quantization algorithm that may be used in connection with the present invention, the image is divided into four-by-four vectors. The mean value of the 16 samples in each four-by-four vector is calculated and subtracted from the vector, leaving a zero-mean residual. The mean values are transmitted separately using a lossless encoding system. A two-dimensional predictor is used so that the mean values are reconstructed within each frame. The prediction error signal is Huffman coded, and the results are placed into a buffer store for later use.
Although digital video systems achieve high picture quality, it is anticipated that picture-in-picture (PIP) will become a preferred feature. Accordingly, a primary goal of the present invention is to provide methods and apparatus for efficiently producing a PIP video signal. U.S. Pat. No. 5,138,455 (Okumura et al.), Aug. 11, 1992, discloses a video signal processing circuit for providing a compressed picture insertion function in a television receiver. This circuit, however, is not especially suited for use with systems which employ compression techniques such as Vector Quantization and/or Statistical Coding. Thus, a further goal of the present invention is to provide methods and apparatus that take advantage of the mean value data produced by such compression techniques to produce a PIP video signal. The present invention achieves these goals.